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AI

THIS IS A MOCKUP VERSION PLEASE DO NOT CITE

AI Skills assess understanding and recognition of artificial intelligence in everyday applications: recognizing when websites/apps use AI, identifying AI-recommended content, and understanding how AI personalizes digital experiences.

AI Skills

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  • Wave 1
  • Wave 2
  • Over Time
  • Overall
  • Age
  • Gender
  • Education
  • Question 1
  • Question 2
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  • Overall
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  • Gender
  • Education
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  • Gender
  • Education
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AI Knowledge

AI Skills assess understanding and recognition of artificial intelligence in everyday applications: recognizing when websites/apps use AI, identifying AI-recommended content, and understanding how AI personalizes digital experiences.

The following statements are about the internet. Please indicate if the sentence is true or untrue, according to you. If you don't know, please choose 'I don't know'. You don't have to guess. If you don't understand the question, please choose 'I don't understand the question.' Nearly everyone will not know or understand questions. This is normal and something that we want to know.
  • Wave 1
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  • Over Time
  • Overall
  • Age
  • Gender
  • Education
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  • Gender
  • Education
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  • Gender
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AI Performance

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  • Overall
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  • Gender
  • Education
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  • Age
  • Gender
  • Education
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  • Gender
  • Education
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  • Question 9
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Source Code
---
title: "{{< iconify ph robot-fill >}} AI"
format: html
---

```{r}
#| include: false
library(dashboardr)
```

**THIS IS A MOCKUP VERSION PLEASE DO NOT CITE**

**AI Skills** assess understanding and recognition of artificial intelligence in everyday applications: recognizing when websites/apps use AI, identifying AI-recommended content, and understanding how AI personalizes digital experiences.

```{r setup}
#| echo: false
#| warning: false
#| message: false
#| error: false
#| results: 'hide'

# Load required libraries
library(dashboardr)
library(dplyr)
library(highcharter)

# Global chunk options
knitr::opts_chunk$set(
  echo = FALSE,
  warning = FALSE,
  message = FALSE,
  error = FALSE,
  fig.width = 12,
  fig.height = 8,
  dpi = 300
)

# Load data from dataset_4014obs.rds
data <- readRDS('dataset_4014obs.rds')

# Data summary
cat('Dataset loaded:', nrow(data), 'rows,', ncol(data), 'columns\n')

# Create filtered datasets
# Each filter is applied once and reused across visualizations

data_filtered_984a0efe <- data %>% dplyr::filter(wave == 1)
data_filtered_4af682fd <- data %>% dplyr::filter(wave == 2)

```

## {{< iconify ph lightning-fill >}} AI Skills


ADD TEXT BEFORE TABSET


::: {.panel-tabset}

### {{< iconify ph number-circle-one-fill >}} Wave 1


::: {.panel-tabset}

##### {{< iconify ph users-fill >}} Overall


```{r ai-wave1-overall-2}
# AI Skills
result <- create_stackedbars(
  data = data_filtered_984a0efe %>% tidyr::drop_na(SAI1, SAI2),
  title = "AI Skills",
  questions = c("SAI1", "SAI2"),
  question_labels = c("I recognize when a website or app uses AI to adjust the content to me.", "I recognize when specific content is recommended to me by AI."),
  stacked_type = "percent",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  horizontal = TRUE,
  x_label = "",
  stack_breaks = c(0.5, 2.5, 3.5, 5.5),
  stack_bin_labels = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  stack_order = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  stack_label = NULL,
  weight_var = "weging_GAMO"
)

result
```


##### {{< iconify mdi:human-male-male-child >}} Age


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r ai-wave1-age-item1-2}
# I recognize when a website or app uses AI to adjust the content to me.
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, SAI1),
  title = "I recognize when a website or app uses AI to adjust the content to me.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0.5, 2.5, 3.5, 5.5),
  stack_bin_labels = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  stack_order = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "SAI1"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r ai-wave1-age-item2-2}
# I recognize when specific content is recommended to me by AI.
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, SAI2),
  title = "I recognize when specific content is recommended to me by AI.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0.5, 2.5, 3.5, 5.5),
  stack_bin_labels = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  stack_order = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "SAI2"
)

result
```


:::


##### {{< iconify mdi gender-transgender >}} Gender


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r ai-wave1-gender-item1-2}
# I recognize when a website or app uses AI to adjust the content to me.
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, SAI1),
  title = "I recognize when a website or app uses AI to adjust the content to me.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0.5, 2.5, 3.5, 5.5),
  stack_bin_labels = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  stack_order = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "SAI1"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r ai-wave1-gender-item2-2}
# I recognize when specific content is recommended to me by AI.
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, SAI2),
  title = "I recognize when specific content is recommended to me by AI.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0.5, 2.5, 3.5, 5.5),
  stack_bin_labels = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  stack_order = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "SAI2"
)

result
```


:::


##### {{< iconify ph graduation-cap-fill >}} Education


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r ai-wave1-edu-item1-2}
# I recognize when a website or app uses AI to adjust the content to me.
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(Education, SAI1),
  title = "I recognize when a website or app uses AI to adjust the content to me.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0.5, 2.5, 3.5, 5.5),
  stack_bin_labels = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  stack_order = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "SAI1"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r ai-wave1-edu-item2-2}
# I recognize when specific content is recommended to me by AI.
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(Education, SAI2),
  title = "I recognize when specific content is recommended to me by AI.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0.5, 2.5, 3.5, 5.5),
  stack_bin_labels = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  stack_order = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "SAI2"
)

result
```


:::


:::


### {{< iconify ph number-circle-two-fill >}} Wave 2


::: {.panel-tabset}

##### {{< iconify ph users-fill >}} Overall


```{r ai-wave2-overall-2}
# AI Skills
result <- create_stackedbars(
  data = data_filtered_4af682fd %>% tidyr::drop_na(SAI1, SAI2),
  title = "AI Skills",
  questions = c("SAI1", "SAI2"),
  question_labels = c("I recognize when a website or app uses AI to adjust the content to me.", "I recognize when specific content is recommended to me by AI."),
  stacked_type = "percent",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  horizontal = TRUE,
  x_label = "",
  stack_breaks = c(0.5, 2.5, 3.5, 5.5),
  stack_bin_labels = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  stack_order = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  stack_label = NULL,
  weight_var = "weging_GAMO"
)

result
```


##### {{< iconify mdi:human-male-male-child >}} Age


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r ai-wave2-age-item1-2}
# I recognize when a website or app uses AI to adjust the content to me.
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, SAI1),
  title = "I recognize when a website or app uses AI to adjust the content to me.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0.5, 2.5, 3.5, 5.5),
  stack_bin_labels = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  stack_order = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "SAI1"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r ai-wave2-age-item2-2}
# I recognize when specific content is recommended to me by AI.
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, SAI2),
  title = "I recognize when specific content is recommended to me by AI.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0.5, 2.5, 3.5, 5.5),
  stack_bin_labels = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  stack_order = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "SAI2"
)

result
```


:::


##### {{< iconify mdi gender-transgender >}} Gender


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r ai-wave2-gender-item1-2}
# I recognize when a website or app uses AI to adjust the content to me.
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, SAI1),
  title = "I recognize when a website or app uses AI to adjust the content to me.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0.5, 2.5, 3.5, 5.5),
  stack_bin_labels = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  stack_order = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "SAI1"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r ai-wave2-gender-item2-2}
# I recognize when specific content is recommended to me by AI.
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, SAI2),
  title = "I recognize when specific content is recommended to me by AI.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0.5, 2.5, 3.5, 5.5),
  stack_bin_labels = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  stack_order = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "SAI2"
)

result
```


:::


##### {{< iconify ph graduation-cap-fill >}} Education


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r ai-wave2-edu-item1-2}
# I recognize when a website or app uses AI to adjust the content to me.
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(Education, SAI1),
  title = "I recognize when a website or app uses AI to adjust the content to me.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0.5, 2.5, 3.5, 5.5),
  stack_bin_labels = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  stack_order = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "SAI1"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r ai-wave2-edu-item2-2}
# I recognize when specific content is recommended to me by AI.
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(Education, SAI2),
  title = "I recognize when specific content is recommended to me by AI.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0.5, 2.5, 3.5, 5.5),
  stack_bin_labels = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  stack_order = c("(Completely) Untrue (1-2)", "Not true and not untrue (3)", "(Completely) True (4-5)"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "SAI2"
)

result
```


:::


:::


### {{< iconify ph chart-line-fill >}} Over Time


::: {.panel-tabset}

##### {{< iconify ph users-fill >}} Overall


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r ai-overtime-overall-item1-2}
# I recognize when a website or app uses AI to adjust the content to me.
result <- create_timeline(
  data = data,
  title = "I recognize when a website or app uses AI to adjust the content to me.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = c(4, 5),
  response_filter_label = "Percentage who answered (Completely) True (4-5)",
  response_filter_combine = TRUE,
  x_label = "",
  y_label = "Percentage who answered (Completely) True (4-5)",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  y_min = 0,
  y_max = 100,
  response_var = "SAI1"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r ai-overtime-overall-item2-2}
# I recognize when specific content is recommended to me by AI.
result <- create_timeline(
  data = data,
  title = "I recognize when specific content is recommended to me by AI.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = c(4, 5),
  response_filter_label = "Percentage who answered (Completely) True (4-5)",
  response_filter_combine = TRUE,
  x_label = "",
  y_label = "Percentage who answered (Completely) True (4-5)",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  y_min = 0,
  y_max = 100,
  response_var = "SAI2"
)

result
```


:::


##### {{< iconify mdi:human-male-male-child >}} Age


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r ai-overtime-age-item1-2}
# I recognize when a website or app uses AI to adjust the content to me.
result <- create_timeline(
  data = data,
  title = "I recognize when a website or app uses AI to adjust the content to me.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = c(4, 5),
  x_label = "",
  y_label = "Percentage who answered (Completely) True (4-5)",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  y_min = 0,
  y_max = 100,
  weight_var = "weging_GAMO",
  response_var = "SAI1",
  group_var = "AgeGroup"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r ai-overtime-age-item2-2}
# I recognize when specific content is recommended to me by AI.
result <- create_timeline(
  data = data,
  title = "I recognize when specific content is recommended to me by AI.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = c(4, 5),
  x_label = "",
  y_label = "Percentage who answered (Completely) True (4-5)",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  y_min = 0,
  y_max = 100,
  weight_var = "weging_GAMO",
  response_var = "SAI2",
  group_var = "AgeGroup"
)

result
```


:::


##### {{< iconify mdi gender-transgender >}} Gender


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r ai-overtime-gender-item1-2}
# I recognize when a website or app uses AI to adjust the content to me.
result <- create_timeline(
  data = data,
  title = "I recognize when a website or app uses AI to adjust the content to me.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = c(4, 5),
  x_label = "",
  y_label = "Percentage who answered (Completely) True (4-5)",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  y_min = 0,
  y_max = 100,
  weight_var = "weging_GAMO",
  response_var = "SAI1",
  group_var = "geslacht"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r ai-overtime-gender-item2-2}
# I recognize when specific content is recommended to me by AI.
result <- create_timeline(
  data = data,
  title = "I recognize when specific content is recommended to me by AI.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = c(4, 5),
  x_label = "",
  y_label = "Percentage who answered (Completely) True (4-5)",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  y_min = 0,
  y_max = 100,
  weight_var = "weging_GAMO",
  response_var = "SAI2",
  group_var = "geslacht"
)

result
```


:::


##### {{< iconify ph graduation-cap-fill >}} Education


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r ai-overtime-edu-item1-2}
# I recognize when a website or app uses AI to adjust the content to me.
result <- create_timeline(
  data = data,
  title = "I recognize when a website or app uses AI to adjust the content to me.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = c(4, 5),
  x_label = "",
  y_label = "Percentage who answered (Completely) True (4-5)",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  y_min = 0,
  y_max = 100,
  weight_var = "weging_GAMO",
  response_var = "SAI1",
  group_var = "Education"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r ai-overtime-edu-item2-2}
# I recognize when specific content is recommended to me by AI.
result <- create_timeline(
  data = data,
  title = "I recognize when specific content is recommended to me by AI.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = c(4, 5),
  x_label = "",
  y_label = "Percentage who answered (Completely) True (4-5)",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  y_min = 0,
  y_max = 100,
  weight_var = "weging_GAMO",
  response_var = "SAI2",
  group_var = "Education"
)

result
```


:::


:::


:::

## {{< iconify ph book-open-fill >}} AI Knowledge


**AI Skills** assess understanding and recognition of artificial intelligence in everyday applications: recognizing when websites/apps use AI, identifying AI-recommended content, and understanding how AI personalizes digital experiences.

```{r, echo=FALSE, message=FALSE, warning=FALSE}
create_blockquote("The following statements are about the internet. Please indicate if the sentence is true or untrue, according to you. If you don't know, please choose 'I don't know'. You don't have to guess. If you don't understand the question, please choose 'I don't understand the question.' Nearly everyone will not know or understand questions. This is normal and something that we want to know.", preset = "question")
```


::: {.panel-tabset}

### {{< iconify ph number-circle-one-fill >}} Wave 1


::: {.panel-tabset}

##### {{< iconify ph users-fill >}} Overall


```{r kai-wave1-overall-2}
# 
result <- create_stackedbars(
  data = data_filtered_984a0efe %>% tidyr::drop_na(KAI1RC, KAI2RC, KAI3RC, KAI4RC),
  title = "",
  questions = c("KAI1RC", "KAI2RC", "KAI3RC", "KAI4RC"),
  question_labels = c("Some websites and apps for news and entertainment use artificial intelligence (AI).", "Websites and apps for news and entertainment show the same content to everyone.", "Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.", "Your online behavior determines what is shown to you on websites and apps for news and entertainment."),
  stacked_type = "percent",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  horizontal = TRUE,
  x_label = "",
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_label = NULL,
  weight_var = "weging_GAMO"
)

result
```


##### {{< iconify mdi:human-male-male-child >}} Age


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r kai-wave1-age-item1-2}
# Some websites and apps for news and entertainment use artificial intelligence (AI).
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, KAI1RC),
  title = "Some websites and apps for news and entertainment use artificial intelligence (AI).",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "KAI1RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r kai-wave1-age-item2-2}
# Websites and apps for news and entertainment show the same content to everyone.
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, KAI2RC),
  title = "Websites and apps for news and entertainment show the same content to everyone.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "KAI2RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r kai-wave1-age-item3-2}
# Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, KAI3RC),
  title = "Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "KAI3RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r kai-wave1-age-item4-2}
# Your online behavior determines what is shown to you on websites and apps for news and entertainment.
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, KAI4RC),
  title = "Your online behavior determines what is shown to you on websites and apps for news and entertainment.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "KAI4RC"
)

result
```


:::


##### {{< iconify mdi gender-transgender >}} Gender


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r kai-wave1-gender-item1-2}
# Some websites and apps for news and entertainment use artificial intelligence (AI).
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, KAI1RC),
  title = "Some websites and apps for news and entertainment use artificial intelligence (AI).",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "KAI1RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r kai-wave1-gender-item2-2}
# Websites and apps for news and entertainment show the same content to everyone.
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, KAI2RC),
  title = "Websites and apps for news and entertainment show the same content to everyone.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "KAI2RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r kai-wave1-gender-item3-2}
# Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, KAI3RC),
  title = "Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "KAI3RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r kai-wave1-gender-item4-2}
# Your online behavior determines what is shown to you on websites and apps for news and entertainment.
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, KAI4RC),
  title = "Your online behavior determines what is shown to you on websites and apps for news and entertainment.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "KAI4RC"
)

result
```


:::


##### {{< iconify ph graduation-cap-fill >}} Education


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r kai-wave1-edu-item1-2}
# Some websites and apps for news and entertainment use artificial intelligence (AI).
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(Education, KAI1RC),
  title = "Some websites and apps for news and entertainment use artificial intelligence (AI).",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "KAI1RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r kai-wave1-edu-item2-2}
# Websites and apps for news and entertainment show the same content to everyone.
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(Education, KAI2RC),
  title = "Websites and apps for news and entertainment show the same content to everyone.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "KAI2RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r kai-wave1-edu-item3-2}
# Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(Education, KAI3RC),
  title = "Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "KAI3RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r kai-wave1-edu-item4-2}
# Your online behavior determines what is shown to you on websites and apps for news and entertainment.
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(Education, KAI4RC),
  title = "Your online behavior determines what is shown to you on websites and apps for news and entertainment.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "KAI4RC"
)

result
```


:::


:::


### {{< iconify ph number-circle-two-fill >}} Wave 2


::: {.panel-tabset}

##### {{< iconify ph users-fill >}} Overall


```{r kai-wave2-overall-2}
# 
result <- create_stackedbars(
  data = data_filtered_4af682fd %>% tidyr::drop_na(KAI1RC, KAI2RC, KAI3RC, KAI4RC),
  title = "",
  questions = c("KAI1RC", "KAI2RC", "KAI3RC", "KAI4RC"),
  question_labels = c("Some websites and apps for news and entertainment use artificial intelligence (AI).", "Websites and apps for news and entertainment show the same content to everyone.", "Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.", "Your online behavior determines what is shown to you on websites and apps for news and entertainment."),
  stacked_type = "percent",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  horizontal = TRUE,
  x_label = "",
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_label = NULL,
  weight_var = "weging_GAMO"
)

result
```


##### {{< iconify mdi:human-male-male-child >}} Age


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r kai-wave2-age-item1-2}
# Some websites and apps for news and entertainment use artificial intelligence (AI).
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, KAI1RC),
  title = "Some websites and apps for news and entertainment use artificial intelligence (AI).",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "KAI1RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r kai-wave2-age-item2-2}
# Websites and apps for news and entertainment show the same content to everyone.
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, KAI2RC),
  title = "Websites and apps for news and entertainment show the same content to everyone.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "KAI2RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r kai-wave2-age-item3-2}
# Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, KAI3RC),
  title = "Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "KAI3RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r kai-wave2-age-item4-2}
# Your online behavior determines what is shown to you on websites and apps for news and entertainment.
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, KAI4RC),
  title = "Your online behavior determines what is shown to you on websites and apps for news and entertainment.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "KAI4RC"
)

result
```


:::


##### {{< iconify mdi gender-transgender >}} Gender


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r kai-wave2-gender-item1-2}
# Some websites and apps for news and entertainment use artificial intelligence (AI).
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, KAI1RC),
  title = "Some websites and apps for news and entertainment use artificial intelligence (AI).",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "KAI1RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r kai-wave2-gender-item2-2}
# Websites and apps for news and entertainment show the same content to everyone.
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, KAI2RC),
  title = "Websites and apps for news and entertainment show the same content to everyone.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "KAI2RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r kai-wave2-gender-item3-2}
# Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, KAI3RC),
  title = "Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "KAI3RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r kai-wave2-gender-item4-2}
# Your online behavior determines what is shown to you on websites and apps for news and entertainment.
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, KAI4RC),
  title = "Your online behavior determines what is shown to you on websites and apps for news and entertainment.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "KAI4RC"
)

result
```


:::


##### {{< iconify ph graduation-cap-fill >}} Education


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r kai-wave2-edu-item1-2}
# Some websites and apps for news and entertainment use artificial intelligence (AI).
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(Education, KAI1RC),
  title = "Some websites and apps for news and entertainment use artificial intelligence (AI).",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "KAI1RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r kai-wave2-edu-item2-2}
# Websites and apps for news and entertainment show the same content to everyone.
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(Education, KAI2RC),
  title = "Websites and apps for news and entertainment show the same content to everyone.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "KAI2RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r kai-wave2-edu-item3-2}
# Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(Education, KAI3RC),
  title = "Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "KAI3RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r kai-wave2-edu-item4-2}
# Your online behavior determines what is shown to you on websites and apps for news and entertainment.
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(Education, KAI4RC),
  title = "Your online behavior determines what is shown to you on websites and apps for news and entertainment.",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  stack_map_values = list("1" = "Correctly Answered", "0" = "Incorrectly Answered"),
  stack_order = c("Don't Know", "Correctly Answered", "Incorrectly Answered"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "KAI4RC"
)

result
```


:::


:::


### {{< iconify ph chart-line-fill >}} Over Time


::: {.panel-tabset}

##### {{< iconify ph users-fill >}} Overall


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r kai-overtime-overall-item1-2}
# Some websites and apps for news and entertainment use artificial intelligence (AI).
result <- create_timeline(
  data = data,
  title = "Some websites and apps for news and entertainment use artificial intelligence (AI).",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  response_filter_label = "Percentage who selected/answered correctly",
  response_filter_combine = TRUE,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  response_var = "KAI1RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r kai-overtime-overall-item2-2}
# Websites and apps for news and entertainment show the same content to everyone.
result <- create_timeline(
  data = data,
  title = "Websites and apps for news and entertainment show the same content to everyone.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  response_filter_label = "Percentage who selected/answered correctly",
  response_filter_combine = TRUE,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  response_var = "KAI2RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r kai-overtime-overall-item3-2}
# Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.
result <- create_timeline(
  data = data,
  title = "Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  response_filter_label = "Percentage who selected/answered correctly",
  response_filter_combine = TRUE,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  response_var = "KAI3RC"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r kai-overtime-overall-item4-2}
# Your online behavior determines what is shown to you on websites and apps for news and entertainment.
result <- create_timeline(
  data = data,
  title = "Your online behavior determines what is shown to you on websites and apps for news and entertainment.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  response_filter_label = "Percentage who selected/answered correctly",
  response_filter_combine = TRUE,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  response_var = "KAI4RC"
)

result
```


:::


##### {{< iconify mdi:human-male-male-child >}} Age


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r kai-overtime-age-item1-2}
# Some websites and apps for news and entertainment use artificial intelligence (AI).
result <- create_timeline(
  data = data,
  title = "Some websites and apps for news and entertainment use artificial intelligence (AI).",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "KAI1RC",
  group_var = "AgeGroup"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r kai-overtime-age-item2-2}
# Websites and apps for news and entertainment show the same content to everyone.
result <- create_timeline(
  data = data,
  title = "Websites and apps for news and entertainment show the same content to everyone.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "KAI2RC",
  group_var = "AgeGroup"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r kai-overtime-age-item3-2}
# Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.
result <- create_timeline(
  data = data,
  title = "Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "KAI3RC",
  group_var = "AgeGroup"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r kai-overtime-age-item4-2}
# Your online behavior determines what is shown to you on websites and apps for news and entertainment.
result <- create_timeline(
  data = data,
  title = "Your online behavior determines what is shown to you on websites and apps for news and entertainment.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "KAI4RC",
  group_var = "AgeGroup"
)

result
```


:::


##### {{< iconify mdi gender-transgender >}} Gender


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r kai-overtime-gender-item1-2}
# Some websites and apps for news and entertainment use artificial intelligence (AI).
result <- create_timeline(
  data = data,
  title = "Some websites and apps for news and entertainment use artificial intelligence (AI).",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "KAI1RC",
  group_var = "geslacht"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r kai-overtime-gender-item2-2}
# Websites and apps for news and entertainment show the same content to everyone.
result <- create_timeline(
  data = data,
  title = "Websites and apps for news and entertainment show the same content to everyone.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "KAI2RC",
  group_var = "geslacht"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r kai-overtime-gender-item3-2}
# Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.
result <- create_timeline(
  data = data,
  title = "Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "KAI3RC",
  group_var = "geslacht"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r kai-overtime-gender-item4-2}
# Your online behavior determines what is shown to you on websites and apps for news and entertainment.
result <- create_timeline(
  data = data,
  title = "Your online behavior determines what is shown to you on websites and apps for news and entertainment.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "KAI4RC",
  group_var = "geslacht"
)

result
```


:::


##### {{< iconify ph graduation-cap-fill >}} Education


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r kai-overtime-edu-item1-2}
# Some websites and apps for news and entertainment use artificial intelligence (AI).
result <- create_timeline(
  data = data,
  title = "Some websites and apps for news and entertainment use artificial intelligence (AI).",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "KAI1RC",
  group_var = "Education"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r kai-overtime-edu-item2-2}
# Websites and apps for news and entertainment show the same content to everyone.
result <- create_timeline(
  data = data,
  title = "Websites and apps for news and entertainment show the same content to everyone.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "KAI2RC",
  group_var = "Education"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r kai-overtime-edu-item3-2}
# Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.
result <- create_timeline(
  data = data,
  title = "Some decisions about the content of websites and apps for news and entertainment are automatic, without a human doing something.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "KAI3RC",
  group_var = "Education"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r kai-overtime-edu-item4-2}
# Your online behavior determines what is shown to you on websites and apps for news and entertainment.
result <- create_timeline(
  data = data,
  title = "Your online behavior determines what is shown to you on websites and apps for news and entertainment.",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "KAI4RC",
  group_var = "Education"
)

result
```


:::


:::


:::

## {{< iconify ph clipboard-text >}} AI Performance


ADD TEXT BEFORE TABSET


::: {.panel-tabset}

### {{< iconify ph number-circle-one-fill >}} Wave 1


::: {.panel-tabset}

##### {{< iconify ph users-fill >}} Overall


```{r perf-ai-wave1-overall-2}
# 
result <- create_stackedbars(
  data = data_filtered_984a0efe %>% tidyr::drop_na(PAIS2_1, PAIS2_2, PAIS2_3, PAIS2_4, PAIS2_5, PAIS2_6, PAIS2_7, PAIS2_8, PAIS2_9),
  title = "",
  questions = c("PAIS2_1", "PAIS2_2", "PAIS2_3", "PAIS2_4", "PAIS2_5", "PAIS2_6", "PAIS2_7", "PAIS2_8", "PAIS2_9"),
  question_labels = c("Google", "Netflix", "Whatsapp", "Facebook", "Bol.com", "DigID", "NOS News", "Albert Heijn", "TikTok"),
  stacked_type = "percent",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  horizontal = TRUE,
  x_label = "",
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  stack_label = NULL,
  weight_var = "weging_GAMO"
)

result
```


##### {{< iconify mdi:human-male-male-child >}} Age


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r perf-ai-wave1-age-item1-2}
# Google
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS2_1),
  title = "Google",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "PAIS2_1"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r perf-ai-wave1-age-item2-2}
# Netflix
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS2_2),
  title = "Netflix",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "PAIS2_2"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r perf-ai-wave1-age-item3-2}
# Whatsapp
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS2_3),
  title = "Whatsapp",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "PAIS2_3"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r perf-ai-wave1-age-item4-2}
# Facebook
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS2_4),
  title = "Facebook",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "PAIS2_4"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 5


```{r perf-ai-wave1-age-item5-2}
# Bol.com
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS2_5),
  title = "Bol.com",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "PAIS2_5"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 6


```{r perf-ai-wave1-age-item6-2}
# DigID
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS2_6),
  title = "DigID",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "PAIS2_6"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 7


```{r perf-ai-wave1-age-item7-2}
# NOS News
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS2_7),
  title = "NOS News",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "PAIS2_7"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 8


```{r perf-ai-wave1-age-item8-2}
# Albert Heijn
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS2_8),
  title = "Albert Heijn",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "PAIS2_8"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 9


```{r perf-ai-wave1-age-item9-2}
# TikTok
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS2_9),
  title = "TikTok",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "PAIS2_9"
)

result
```


:::


##### {{< iconify mdi gender-transgender >}} Gender


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r perf-ai-wave1-gender-item1-2}
# Google
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS2_1),
  title = "Google",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "PAIS2_1"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r perf-ai-wave1-gender-item2-2}
# Netflix
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS2_2),
  title = "Netflix",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "PAIS2_2"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r perf-ai-wave1-gender-item3-2}
# Whatsapp
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS2_3),
  title = "Whatsapp",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "PAIS2_3"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r perf-ai-wave1-gender-item4-2}
# Facebook
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS2_4),
  title = "Facebook",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "PAIS2_4"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 5


```{r perf-ai-wave1-gender-item5-2}
# Bol.com
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS2_5),
  title = "Bol.com",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "PAIS2_5"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 6


```{r perf-ai-wave1-gender-item6-2}
# DigID
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS2_6),
  title = "DigID",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "PAIS2_6"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 7


```{r perf-ai-wave1-gender-item7-2}
# NOS News
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS2_7),
  title = "NOS News",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "PAIS2_7"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 8


```{r perf-ai-wave1-gender-item8-2}
# Albert Heijn
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS2_8),
  title = "Albert Heijn",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "PAIS2_8"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 9


```{r perf-ai-wave1-gender-item9-2}
# TikTok
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS2_9),
  title = "TikTok",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "PAIS2_9"
)

result
```


:::


##### {{< iconify ph graduation-cap-fill >}} Education


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r perf-ai-wave1-edu-item1-2}
# Google
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS2_1),
  title = "Google",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "PAIS2_1"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r perf-ai-wave1-edu-item2-2}
# Netflix
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS2_2),
  title = "Netflix",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "PAIS2_2"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r perf-ai-wave1-edu-item3-2}
# Whatsapp
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS2_3),
  title = "Whatsapp",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "PAIS2_3"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r perf-ai-wave1-edu-item4-2}
# Facebook
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS2_4),
  title = "Facebook",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "PAIS2_4"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 5


```{r perf-ai-wave1-edu-item5-2}
# Bol.com
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS2_5),
  title = "Bol.com",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "PAIS2_5"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 6


```{r perf-ai-wave1-edu-item6-2}
# DigID
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS2_6),
  title = "DigID",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "PAIS2_6"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 7


```{r perf-ai-wave1-edu-item7-2}
# NOS News
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS2_7),
  title = "NOS News",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "PAIS2_7"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 8


```{r perf-ai-wave1-edu-item8-2}
# Albert Heijn
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS2_8),
  title = "Albert Heijn",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "PAIS2_8"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 9


```{r perf-ai-wave1-edu-item9-2}
# TikTok
result <- create_stackedbar(
  data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS2_9),
  title = "TikTok",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "PAIS2_9"
)

result
```


:::


:::


### {{< iconify ph number-circle-two-fill >}} Wave 2


::: {.panel-tabset}

##### {{< iconify ph users-fill >}} Overall


```{r perf-ai-wave2-overall-2}
# 
result <- create_stackedbars(
  data = data_filtered_4af682fd %>% tidyr::drop_na(PAIS2_1, PAIS2_2, PAIS2_3, PAIS2_4, PAIS2_5, PAIS2_6, PAIS2_7, PAIS2_8, PAIS2_9),
  title = "",
  questions = c("PAIS2_1", "PAIS2_2", "PAIS2_3", "PAIS2_4", "PAIS2_5", "PAIS2_6", "PAIS2_7", "PAIS2_8", "PAIS2_9"),
  question_labels = c("Google", "Netflix", "Whatsapp", "Facebook", "Bol.com", "DigID", "NOS News", "Albert Heijn", "TikTok"),
  stacked_type = "percent",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  horizontal = TRUE,
  x_label = "",
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  stack_label = NULL,
  weight_var = "weging_GAMO"
)

result
```


##### {{< iconify mdi:human-male-male-child >}} Age


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r perf-ai-wave2-age-item1-2}
# Google
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS2_1),
  title = "Google",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "PAIS2_1"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r perf-ai-wave2-age-item2-2}
# Netflix
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS2_2),
  title = "Netflix",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "PAIS2_2"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r perf-ai-wave2-age-item3-2}
# Whatsapp
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS2_3),
  title = "Whatsapp",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "PAIS2_3"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r perf-ai-wave2-age-item4-2}
# Facebook
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS2_4),
  title = "Facebook",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "PAIS2_4"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 5


```{r perf-ai-wave2-age-item5-2}
# Bol.com
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS2_5),
  title = "Bol.com",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "PAIS2_5"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 6


```{r perf-ai-wave2-age-item6-2}
# DigID
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS2_6),
  title = "DigID",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "PAIS2_6"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 7


```{r perf-ai-wave2-age-item7-2}
# NOS News
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS2_7),
  title = "NOS News",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "PAIS2_7"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 8


```{r perf-ai-wave2-age-item8-2}
# Albert Heijn
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS2_8),
  title = "Albert Heijn",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "PAIS2_8"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 9


```{r perf-ai-wave2-age-item9-2}
# TikTok
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS2_9),
  title = "TikTok",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "AgeGroup",
  stack_var = "PAIS2_9"
)

result
```


:::


##### {{< iconify mdi gender-transgender >}} Gender


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r perf-ai-wave2-gender-item1-2}
# Google
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS2_1),
  title = "Google",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "PAIS2_1"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r perf-ai-wave2-gender-item2-2}
# Netflix
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS2_2),
  title = "Netflix",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "PAIS2_2"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r perf-ai-wave2-gender-item3-2}
# Whatsapp
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS2_3),
  title = "Whatsapp",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "PAIS2_3"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r perf-ai-wave2-gender-item4-2}
# Facebook
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS2_4),
  title = "Facebook",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "PAIS2_4"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 5


```{r perf-ai-wave2-gender-item5-2}
# Bol.com
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS2_5),
  title = "Bol.com",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "PAIS2_5"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 6


```{r perf-ai-wave2-gender-item6-2}
# DigID
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS2_6),
  title = "DigID",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "PAIS2_6"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 7


```{r perf-ai-wave2-gender-item7-2}
# NOS News
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS2_7),
  title = "NOS News",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "PAIS2_7"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 8


```{r perf-ai-wave2-gender-item8-2}
# Albert Heijn
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS2_8),
  title = "Albert Heijn",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "PAIS2_8"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 9


```{r perf-ai-wave2-gender-item9-2}
# TikTok
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS2_9),
  title = "TikTok",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "geslacht",
  stack_var = "PAIS2_9"
)

result
```


:::


##### {{< iconify ph graduation-cap-fill >}} Education


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r perf-ai-wave2-edu-item1-2}
# Google
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS2_1),
  title = "Google",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "PAIS2_1"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r perf-ai-wave2-edu-item2-2}
# Netflix
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS2_2),
  title = "Netflix",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "PAIS2_2"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r perf-ai-wave2-edu-item3-2}
# Whatsapp
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS2_3),
  title = "Whatsapp",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "PAIS2_3"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r perf-ai-wave2-edu-item4-2}
# Facebook
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS2_4),
  title = "Facebook",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "PAIS2_4"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 5


```{r perf-ai-wave2-edu-item5-2}
# Bol.com
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS2_5),
  title = "Bol.com",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "PAIS2_5"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 6


```{r perf-ai-wave2-edu-item6-2}
# DigID
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS2_6),
  title = "DigID",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "PAIS2_6"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 7


```{r perf-ai-wave2-edu-item7-2}
# NOS News
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS2_7),
  title = "NOS News",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "PAIS2_7"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 8


```{r perf-ai-wave2-edu-item8-2}
# Albert Heijn
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS2_8),
  title = "Albert Heijn",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "PAIS2_8"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 9


```{r perf-ai-wave2-edu-item9-2}
# TikTok
result <- create_stackedbar(
  data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS2_9),
  title = "TikTok",
  stacked_type = "percent",
  horizontal = TRUE,
  stack_breaks = c(0, 10, 20, 30),
  stack_bin_labels = c("Not selected", "Selected"),
  stack_map_values = list("1" = "Selected", "0" = "Not selected"),
  stack_order = c("Not selected", "Selected"),
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  x_var = "Education",
  stack_var = "PAIS2_9"
)

result
```


:::


:::


### {{< iconify ph chart-line-fill >}} Over Time


::: {.panel-tabset}

##### {{< iconify ph users-fill >}} Overall


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r perf-ai-overtime-overall-item1-2}
# Google
result <- create_timeline(
  data = data,
  title = "Google",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  response_filter_label = "Percentage who selected/answered correctly",
  response_filter_combine = TRUE,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  response_var = "PAIS2_1"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r perf-ai-overtime-overall-item2-2}
# Netflix
result <- create_timeline(
  data = data,
  title = "Netflix",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  response_filter_label = "Percentage who selected/answered correctly",
  response_filter_combine = TRUE,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  response_var = "PAIS2_2"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r perf-ai-overtime-overall-item3-2}
# Whatsapp
result <- create_timeline(
  data = data,
  title = "Whatsapp",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  response_filter_label = "Percentage who selected/answered correctly",
  response_filter_combine = TRUE,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  response_var = "PAIS2_3"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r perf-ai-overtime-overall-item4-2}
# Facebook
result <- create_timeline(
  data = data,
  title = "Facebook",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  response_filter_label = "Percentage who selected/answered correctly",
  response_filter_combine = TRUE,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  response_var = "PAIS2_4"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 5


```{r perf-ai-overtime-overall-item5-2}
# Bol.com
result <- create_timeline(
  data = data,
  title = "Bol.com",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  response_filter_label = "Percentage who selected/answered correctly",
  response_filter_combine = TRUE,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  response_var = "PAIS2_5"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 6


```{r perf-ai-overtime-overall-item6-2}
# DigID
result <- create_timeline(
  data = data,
  title = "DigID",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  response_filter_label = "Percentage who selected/answered correctly",
  response_filter_combine = TRUE,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  response_var = "PAIS2_6"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 7


```{r perf-ai-overtime-overall-item7-2}
# NOS News
result <- create_timeline(
  data = data,
  title = "NOS News",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  response_filter_label = "Percentage who selected/answered correctly",
  response_filter_combine = TRUE,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  response_var = "PAIS2_7"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 8


```{r perf-ai-overtime-overall-item8-2}
# Albert Heijn
result <- create_timeline(
  data = data,
  title = "Albert Heijn",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  response_filter_label = "Percentage who selected/answered correctly",
  response_filter_combine = TRUE,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  response_var = "PAIS2_8"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 9


```{r perf-ai-overtime-overall-item9-2}
# TikTok
result <- create_timeline(
  data = data,
  title = "TikTok",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  response_filter_label = "Percentage who selected/answered correctly",
  response_filter_combine = TRUE,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  weight_var = "weging_GAMO",
  response_var = "PAIS2_9"
)

result
```


:::


##### {{< iconify mdi:human-male-male-child >}} Age


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r perf-ai-overtime-age-item1-2}
# Google
result <- create_timeline(
  data = data,
  title = "Google",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_1",
  group_var = "AgeGroup"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r perf-ai-overtime-age-item2-2}
# Netflix
result <- create_timeline(
  data = data,
  title = "Netflix",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_2",
  group_var = "AgeGroup"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r perf-ai-overtime-age-item3-2}
# Whatsapp
result <- create_timeline(
  data = data,
  title = "Whatsapp",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_3",
  group_var = "AgeGroup"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r perf-ai-overtime-age-item4-2}
# Facebook
result <- create_timeline(
  data = data,
  title = "Facebook",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_4",
  group_var = "AgeGroup"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 5


```{r perf-ai-overtime-age-item5-2}
# Bol.com
result <- create_timeline(
  data = data,
  title = "Bol.com",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_5",
  group_var = "AgeGroup"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 6


```{r perf-ai-overtime-age-item6-2}
# DigID
result <- create_timeline(
  data = data,
  title = "DigID",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_6",
  group_var = "AgeGroup"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 7


```{r perf-ai-overtime-age-item7-2}
# NOS News
result <- create_timeline(
  data = data,
  title = "NOS News",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_7",
  group_var = "AgeGroup"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 8


```{r perf-ai-overtime-age-item8-2}
# Albert Heijn
result <- create_timeline(
  data = data,
  title = "Albert Heijn",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_8",
  group_var = "AgeGroup"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 9


```{r perf-ai-overtime-age-item9-2}
# TikTok
result <- create_timeline(
  data = data,
  title = "TikTok",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_9",
  group_var = "AgeGroup"
)

result
```


:::


##### {{< iconify mdi gender-transgender >}} Gender


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r perf-ai-overtime-gender-item1-2}
# Google
result <- create_timeline(
  data = data,
  title = "Google",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_1",
  group_var = "geslacht"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r perf-ai-overtime-gender-item2-2}
# Netflix
result <- create_timeline(
  data = data,
  title = "Netflix",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_2",
  group_var = "geslacht"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r perf-ai-overtime-gender-item3-2}
# Whatsapp
result <- create_timeline(
  data = data,
  title = "Whatsapp",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_3",
  group_var = "geslacht"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r perf-ai-overtime-gender-item4-2}
# Facebook
result <- create_timeline(
  data = data,
  title = "Facebook",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_4",
  group_var = "geslacht"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 5


```{r perf-ai-overtime-gender-item5-2}
# Bol.com
result <- create_timeline(
  data = data,
  title = "Bol.com",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_5",
  group_var = "geslacht"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 6


```{r perf-ai-overtime-gender-item6-2}
# DigID
result <- create_timeline(
  data = data,
  title = "DigID",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_6",
  group_var = "geslacht"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 7


```{r perf-ai-overtime-gender-item7-2}
# NOS News
result <- create_timeline(
  data = data,
  title = "NOS News",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_7",
  group_var = "geslacht"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 8


```{r perf-ai-overtime-gender-item8-2}
# Albert Heijn
result <- create_timeline(
  data = data,
  title = "Albert Heijn",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_8",
  group_var = "geslacht"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 9


```{r perf-ai-overtime-gender-item9-2}
# TikTok
result <- create_timeline(
  data = data,
  title = "TikTok",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_9",
  group_var = "geslacht"
)

result
```


:::


##### {{< iconify ph graduation-cap-fill >}} Education


::: {.panel-tabset}

###### {{< iconify ph chat-circle-fill >}} Question 1


```{r perf-ai-overtime-edu-item1-2}
# Google
result <- create_timeline(
  data = data,
  title = "Google",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_1",
  group_var = "Education"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 2


```{r perf-ai-overtime-edu-item2-2}
# Netflix
result <- create_timeline(
  data = data,
  title = "Netflix",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_2",
  group_var = "Education"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 3


```{r perf-ai-overtime-edu-item3-2}
# Whatsapp
result <- create_timeline(
  data = data,
  title = "Whatsapp",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_3",
  group_var = "Education"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 4


```{r perf-ai-overtime-edu-item4-2}
# Facebook
result <- create_timeline(
  data = data,
  title = "Facebook",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_4",
  group_var = "Education"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 5


```{r perf-ai-overtime-edu-item5-2}
# Bol.com
result <- create_timeline(
  data = data,
  title = "Bol.com",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_5",
  group_var = "Education"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 6


```{r perf-ai-overtime-edu-item6-2}
# DigID
result <- create_timeline(
  data = data,
  title = "DigID",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_6",
  group_var = "Education"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 7


```{r perf-ai-overtime-edu-item7-2}
# NOS News
result <- create_timeline(
  data = data,
  title = "NOS News",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_7",
  group_var = "Education"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 8


```{r perf-ai-overtime-edu-item8-2}
# Albert Heijn
result <- create_timeline(
  data = data,
  title = "Albert Heijn",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_8",
  group_var = "Education"
)

result
```


###### {{< iconify ph chat-circle-fill >}} Question 9


```{r perf-ai-overtime-edu-item9-2}
# TikTok
result <- create_timeline(
  data = data,
  title = "TikTok",
  time_var = "wave_time_label",
  chart_type = "line",
  response_filter = 1,
  y_min = 0,
  y_max = 100,
  x_label = "",
  y_label = "Percentage who selected/answered correctly",
  color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"),
  response_filter_label = NULL,
  weight_var = "weging_GAMO",
  response_var = "PAIS2_9",
  group_var = "Education"
)

result
```


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